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Employees’ Trust in Artificial Intelligence in Companies: The Case of Energy and Chemical Industries in Poland

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  • Justyna Łapińska

    (Department of Organizational Behavior and Marketing, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Iwona Escher

    (Department of Organizational Behavior and Marketing, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Joanna Górka

    (Department of Econometrics and Statistics, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Agata Sudolska

    (Department of Enterprise Management, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

  • Paweł Brzustewicz

    (Department of Organizational Behavior and Marketing, Faculty of Economic Sciences and Management, Nicolaus Copernicus University, 87-100 Toruń, Poland)

Abstract

The use of artificial intelligence (AI) in companies is advancing rapidly. Consequently, multidisciplinary research on AI in business has developed dramatically during the last decade, moving from the focus on technological objectives towards an interest in human users’ perspective. In this article, we investigate the notion of employees’ trust in AI at the workplace (in the company), following a human-centered approach that considers AI integration in business from the employees’ perspective, taking into account the elements that facilitate human trust in AI. While employees’ trust in AI at the workplace seems critical, so far, few studies have systematically investigated its determinants. Therefore, this study is an attempt to fill the existing research gap. The research objective of the article is to examine links between employees’ trust in AI in the company and three other latent variables (general trust in technology, intra-organizational trust, and individual competence trust). A quantitative study conducted on a sample of 428 employees from companies of the energy and chemical industries in Poland allowed the hypotheses to be verified. The hypotheses were tested using structural equation modeling (SEM). The results indicate the existence of a positive relationship between general trust in technology and employees’ trust in AI in the company as well as between intra-organizational trust and employees’ trust in AI in the company in the surveyed firms.

Suggested Citation

  • Justyna Łapińska & Iwona Escher & Joanna Górka & Agata Sudolska & Paweł Brzustewicz, 2021. "Employees’ Trust in Artificial Intelligence in Companies: The Case of Energy and Chemical Industries in Poland," Energies, MDPI, vol. 14(7), pages 1-20, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1942-:d:528443
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    References listed on IDEAS

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    Cited by:

    1. Song, Yuegang & Wang, Ziqi & Song, Changqing & Wang, Jianhua & Liu, Rong, 2024. "Impact of artificial intelligence on renewable energy supply chain vulnerability: Evidence from 61 countries," Energy Economics, Elsevier, vol. 131(C).
    2. Kądzielawski Grzegorz, 2023. "The state of development of artificial intelligence in polish industry: opinions of employees," International Journal of Contemporary Management, Sciendo, vol. 59(1), pages 12-25, March.
    3. Rongbin Yang & Santoso Wibowo, 2022. "User trust in artificial intelligence: A comprehensive conceptual framework," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2053-2077, December.

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